基于动态图像阈值的智能车辆路径导航

Path Tracking of Intelligent Vehicle Based on Dynamic Image Threshold

使用机器视觉技术进行智能车辆车道路径识别时,其识别效果易受光照等外界因素的影响。考虑到条带状的导航路径在获取的路径图像中的宽度应该在一个固定范围内,可以根据使用某一图像阈值识别路径后该路径的横向宽度判定先前使用的阈值是否适合,并进行相应调整,从而获取到适合各种环境的动态阈值。在给出动态图像阈值的获取流程及实现方法的基础上,对智能车辆车道路径识别和跟踪系统进行了软硬件设计,并进行实车道路试验。试验结果表明,与一般最优阈值算法相比,提出的动态阈值方法能够在各种光照条件下,尤其是强光照下准确地识别导航路径,且路径跟踪具有较好的精确性和鲁棒性。

The path recognition for vision-guided intelligent vehicle is easily affected by environmental conditions such as illumination. Considering the width of the path in the captured image should be in a fixed range, the recognized path width could be used to determine whether the previously-used threshold was suitable or not. And then the threshold could be adjusted to a suitable value to recognize the path accurately. The process and method for acquiring the dynamic image threshold was presented, and the path recognition and tracking system was designed. The experiments showed the dynamic image threshold could recognize the path more efficiently than other common optimal threshold algorithm under different conditions, especially under strong illumination, and the intelligent vehicle can track the path accurately and robustly.